I agree. >> Each country would have a specific HIV number and now you're not looking at the right country, so does that make sense? >> I see. Yes, but it's hard for me to articulate what you just said. >> You are embarking on a journey. Perhaps your goals and directions are clear. [MUSIC] Perhaps you have some broad ideas and passion to guide you through your studies. [NOISE] Whatever your journey, you can be certain that it is unique. No one else will follow exactly the same path. Perhaps you're an entrepreneur with innovative ideas for products and services. Perhaps you're seeking a deeper understanding of our universe through science. [MUSIC] Perhaps you're interested in understanding the behavior of individuals, communities, or societies. Or perhaps you're passionate about change, about making the world a better place. Whatever your passion, you can be sure that your journey is unique and yet, you're united by the need to analyze, understand, and describe data. Many students view the development of skills involved in analyzing data as an obstacle to be overcome on their journey. Rather than an obstacle, data analysis skills actually provide a common language that will speed you along. You'll need this language in order to understand what others are saying and to tell your story. That's why this specialization was created. In each course, we'll present statistical and machine learning tools allowing you to analyze and interpret large datasets in the service of your own research questions. Throughout the specialization, you'll be conducting original research, asking original questions, and communicating your methods and results. This is not an academic exercise but rather an opportunity to create new knowledge and to share this understanding with others. It's an opportunity to further your passion. >> In the future, I think it's gonna be really important that we find this subsurface ice to sustain astronauts who may explore Mars one day. >> HIV rate is not significantly correlated to life expectancy in Latin American countries. However, it is significantly correlated in the lowest income group. >> What sets apart the behavior of binge drinkers from people who drink casually, who drink more moderately? >> The total mean of drug usage that was reported by adolescents show that most people were not using drugs. >> This specialization grew out of our National Science Foundation funded Passion-Driven Statistics project. It represents a hands-on project-based approach aimed at getting you working you actively on a research question of your choosing from the very beginning. >> The specialization is designed for students who are interested in developing skills for working with data and using statistical and machine learning tools to analyze them. Absolutely no prior experience with data is required. >> Throughout the specialization, you'll be working with data that already exists. We've chosen a number of datasets that contain vast amounts of information covering drug use, adolescent health, space science and more. From these datasets you'll be able to pose questions of interest to you and then turn raw data into useful information. >> Although our goal is ultimately to present materials across several major platforms used to conduct data analysis, we'll begin with the opportunity to learn either Python or SAS. Both provide outstanding data analysis tools for modern computing with large datasets. To help you decide which you'd like to learn, or at least learn first, we provided a document comparing system requirements and other similarities and differences. >> Whichever you choose, you'll be writing and running your own programs. For some of you who've never written code before, this may seem daunting but don't worry because there's lots of support. Remember, this is data analysis in the service of research questions, your research question always comes first. Finally, you will have the opportunity to use the data analysis skills to work with our industry partner to complete a capstone data analysis project that addresses an important issue in society. When you're done, you will have a high quality report that you can show to professionals and potential employers to demonstrate the skills you've learned. >> Throughout this specialization, we'll not only get you working with a range of statistical and machine learning tools but we'll also get you telling your story, and developing the skills necessary to communicate your findings to both expert and novice audiences. We encourage you to join in the discussions, where you'll find answers to many of your questions, and get both instructor and peer support. Enjoy. >> You find out what pertains to you. You have to figure out what you're genuinely interested in. >> If it's something's that's yours, something you can relate to, there's more of you that goes into it. >> Each student can look at the same dataset but come up with a different research question and they can choose to analyze it in a different way and where they take that is completely their own. Data is just so awesome and I really want students to see that, I want them to experience it. I want them to embrace it and so I just want them to understand that they can take this with them for the rest of their life and it's always going to be valuable. >> This has changed the way that I view the world, this changes the way that I hear about research and literature. It changes everything.